Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11CB2AAF2B42054A303B3A9D4E4B1FF2EA696F30F851A85952EBC44862FC7CF5B541A74 |
|
CONTENT
ssdeep
|
192:6GVRKf26qV4tZFwD08u6QVsysa9q8FhJ68Jh6G83VbQFdFeF0FDM4DdLwRG6c6ky:HAzbwsFdFeF0FDMmt5T+Oqtx9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
db3265663331cc99 |
|
VISUAL
aHash
|
003c3c3c3c3c3c00 |
|
VISUAL
dHash
|
0e69616969617986 |
|
VISUAL
wHash
|
003c3c3c3c3c3c00 |
|
VISUAL
colorHash
|
07001200058 |
|
VISUAL
cropResistant
|
8ec042434e015130,0e69616969617986 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 26 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)